"Voices Help Correlate Signs and Words": Analyzing Deaf and Hard-of-Hearing (DHH) TikTokers' Content, Practices, and Pitfalls

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Abstract

Video-sharing platforms such as TikTok have offered new opportunities for d/Deaf and hard-of-hearing (DHH) people to create public-facing content using sign language - an integral part of DHH culture. Besides sign language, DHH creators deal with a variety of modalities when creating videos, such as captions and audio. However, hardly any work has comprehensively addressed DHH creators' multimodal practices with the lay public's reactions taken into account. In this paper, we systematically analyzed 308 DHH-authored TikTok videos using a mixed-methods approach, focusing on DHH TikTokers' content, practices, pitfalls, and viewer engagement. Our findings highlight that while voice features such as synchronous voices are scant and challenging for DHH TikTokers, they may help promote viewer engagement. Other empirical findings, including the distributions of topics, practices, pitfalls, and their correlations with viewer engagement, further lead to actionable suggestions for DHH TikTokers and video-sharing platforms.

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Cao, J., Peng, X., Liang, F., & Tong, X. (2024). “Voices Help Correlate Signs and Words”: Analyzing Deaf and Hard-of-Hearing (DHH) TikTokers’ Content, Practices, and Pitfalls. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3613904.3642413

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